Hardware Implementation of Heart Rate and QRS Complex Detection Using Raspberry Pi Processor for Medical Diagnosis

Abstract

Electrocardiogram signals are acquired from the human body for the diagnosis of cardiac disorders. The surface electrodes are used for ECG signal acquisition and prior to hear beat detection preprocessing is performed. The FIR band pass filter based on Kaiser window is used for the filtering of the ECG signal. The band pass filtered energy signal is subjected to thresholding algorithm for R peak detection. The heart rate is estimated from the R-R interval. The hybrid filter with thresholding was employed for the QRS complex detection. The algorithms are developed in python and implemented in raspberry Pi embedded processor. The algorithms are evaluated on fantasia ECG data set and satisfactory results are obtained.